Cloud based evaluation of databases for stock market data.

About fifty years ago, the world's first fully automated system for trading securities was introduced by Instinet in the US. Since then the world of trading has been revolutionised by the introduction of electronic markets and automatic order execution. Nowadays, financial institutions exploit the associated flow of daily data using more and more advanced analytics to gain valuable insight on the markets and inform their investment decisions. In particular, time series of Open High Low Close prices and Volume data are of special interest as they allow identifying trading patterns useful for forecasting both stock prices and volumes. Traditionally, relational databases have been used to store this data; however, the ever-growing volume of this data, the adoption of the hybrid cloud model, and the availability of novel non-relational databases which claim to be more scalable and fault tolerant raise the question whether relational databases are still the most appropriate. In this study, we define a set of criteria to evaluate performance of a variety of databases on a hybrid cloud environment. There, we conduct experiments using standard and custom workloads. Results show that migration to a MongoDB database would be most beneficial in terms of cost, storage space, and throughput. In addition, organisations wishing to take advantage of autoscaling and the maintenance power of the cloud should opt for a cloud native solution.

Evaluation of Indirect Methods for Motion Compensation in 2-D Focal Liver Lesion Contrast-Enhanced Ultrasound (CEUS) Imaging.

This study investigates the application and evaluation of existing indirect methods, namely point-based registration techniques, for the estimation and compensation of observed motion included in the 2-D image plane of contrast-enhanced ultrasound (CEUS) cine-loops recorded for the characterization and diagnosis of focal liver lesions (FLLs). The value of applying motion compensation in the challenging modality of CEUS is to assist in the quantification of the perfusion dynamics of an FLL in relation to its parenchyma, allowing for a potentially accurate diagnostic suggestion. Towards this end, this study also proposes a novel quantitative multi-level framework for evaluating the quantification of FLLs, which to the best of our knowledge remains undefined, notwithstanding many relevant studies. Following quantitative evaluation of 19 indirect algorithms and configurations, while also considering the requirement for computational efficiency, our results suggest that the "compact and real-time descriptor" (CARD) is the optimal indirect motion compensation method in CEUS.

Automatic Identification of the Optimal Reference Frame for Segmentation and Quantification of Focal Liver Lesions in Contrast-Enhanced Ultrasound.

Post-examination interpretation of contrast-enhanced ultrasound (CEUS) cineloops of focal liver lesions (FLLs) requires offline manual assessment by experienced radiologists, which is time-consuming and generates subjective results. Such assessment usually starts by manually identifying a reference frame, where FLL and healthy parenchyma are well-distinguished. This study proposes an automatic computational method to objectively identify the optimal reference frame for distinguishing and hence delineating an FLL, by statistically analyzing the temporal intensity variation across the spatially discretized ultrasonographic image. Level of confidence and clinical value of the proposed method were quantitatively evaluated on retrospective multi-institutional data (n = 64) and compared with expert interpretations. Results support the proposed method for facilitating easier, quicker and reproducible assessment of FLLs, further increasing the radiologists' confidence in diagnostic decisions. Finally, our method yields a useful training tool for radiologists, widening CEUS use in non-specialist centers, potentially leading to reduced turnaround times and lower patient anxiety and healthcare costs.

Clinical applications of oxidized zirconium.

Total joint arthroplasty is being performed in younger, more active patients, which necessitates improved implant longevity and enhanced component performance. Over the past decade, there has been an increased focus on alternative bearing materials as a potential solution to these issues. Historically, cobalt-chromium has been the material of choice as a bearing surface for both the femoral component in total knee arthroplasty (TKA) and the femoral head articulation in total hip arthroplasty (THA). In recent years, oxidized zirconium (OxZr) has been introduced as a bearing surface with superior resistance to surface roughening, improved frictional characteristics, and excellent biocompatibility as compared with cobalt-chrome. This article demonstrates the use of OxZr as an alternate bearing in the setting of TKA, THA, and hip hemi-arthroplasty based on its biomaterial properties as it applies to polyethylene and native cartilage surface articulation.